• Journal of Communications and Networks
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• v.16 no.6
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• pp.600-612
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• 2014

In this paper, we consider the problem of spectrum sensing for advanced television systems committee (ATSC) digital television (DTV) signal detection. To exploit the cyclostationarity of the ATSC DTV signals, we employ spectral correlation density (SCD) as the decision statistic and propose an optimal detection algorithm. The major difficulty is in obtaining the probability distribution functions of the SCD. To overcome the difficulty, we probabilistically model the pilot frequency location and employ Gaussian approximation for the SCD distribution. Then, we obtain a practically implementable detection algorithm that outperforms the industry leading systems by 2-3 dB. We also propose various techniques that greatly reduce the system complexity with performance degradation by only a few tenths of decibels. Finally, we show how robust the system is to the estimation errors of the noise power spectral density level and the probability distribution of the pilot frequency location.

• The Korean Journal of Applied Statistics
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• v.3 no.1
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• pp.11-25
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• 1990

The objective of this paper is to propose a nonparametric distribution-free test for ordered alternatives in k crossed factor designs by using the concepts of combined factor and within-blocks ranks. We investigate the asymptotic normality of the proposed test statistic and the Pitman efficiencies. We also compared the small empirical powers of the tests considered in this paper by Monte Carlo study. Thus we can conclude that the proposed test is efficient and robust for the underlying distribution.

• The Korean Journal of Applied Statistics
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• v.7 no.2
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• pp.159-171
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• 1994

Some rank score tests are proposed for testing the equality of all sampling distribution functions against umbrella location-scale alternatives in k-sample problem. Only the case of known peak $\ell$ is considered. Under the null hypothesis and a contiguous sequence of unbrella location-scale alternatives, the asymptotic properties of the proposed test statistics are investigated. Also, the asymptotic local powers are compared with each others. The results show that the tests based on the Chen-Wolfe rank analogue statistic are more powerful than others for unequally spaced umbrella location-scale alternatives and robust.

• International journal of advanced smart convergence
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• v.7 no.4
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• pp.40-49
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• 2018

We propose a more stable robust recognition algorithm which detects faces reliably even in cases where there are changes in lighting and angle of view, as well it satisfies efficiency in calculation and detection performance. We propose detects the face area alone after normalization through pre-processing and obtains a feature vector using (PCA). The feature vector is applied to LDA and using Euclidean distance of intra-class variance and inter class variance in the 2nd dimension, the final analysis and matching is performed. Experimental results show that the proposed method has a wider distribution when the input image is rotated $45^{\circ}$ left / right. We can improve the recognition rate by applying this feature value to a single algorithm and complex algorithm, and it is possible to recognize in real time because it does not require much calculation amount due to dimensional reduction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.1064-1079
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• 2019

Information security has become increasingly important with the rapid development of mobile devices and internet. An efficient encryption system is a key to this end. In this paper, we propose an image encryption method based on the cross diffusion of two chaotic maps. We use two chaotic sequences, namely the Logistic map and the Chebyshev map, for key generation which has larger security key space than single one. Moreover, we use these two sequences for further image encryption diffusion which decreases the correlation of neighboring pixels significantly. We conduct extensive experiments on several well-known images like Lena, Baboon, Koala, etc. Experimental results show that our algorithm has the characteristics of large key space, fast, robust to statistic attack, etc.

• Journal of Advanced Navigation Technology
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• v.12 no.3
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• pp.273-279
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• 2008

In this paper, we proposed a watermarking algorithm by using difference matrix between successive blocks in the transform domain. In the preprocessing, original image is decomposed with 1-level sub-bands by DWT. Then, all sub-bands which are excepted the low-frequency bands are set to normalize and make a reference image after transforming inverse DWT. The statistic variance of successive blocks between the original image and the reference image are calculated and finally, watermark is embedded considering the local characteristic with respect to the high-frequence components. Experimental results showed that the proposed approach is robust and better invisible in such attacks as filtering, JPEG and noise addition.

• Journal of the Korean Statistical Society
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• v.30 no.1
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• pp.41-61
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• 2001

The minimum negative exponential disparity estimator(MNEDE), introduced by Lindsay(1994), is an excellenet competitor to the minimum Hellinger distance estimator(Beran 1977) as a robust and yet efficient alternative to the maximum likelihood estimator in parametric models. In this paper we define the negative exponential deviance test(NEDT) as an analog of the likelihood ratio test(LRT), and show that the NEDT is asymptotically equivalent to he LRT at the model and under a sequence of contiguous alternatives. We establish that the asymptotic strong breakdown point for a class of minimum disparity estimators, containing the MNEDE, is at least 1/2 in continuous models. This result leads us to anticipate robustness of the NEDT under data contamination, and we demonstrate it empirically. In fact, in the simulation settings considered here the empirical level of the NEDT show more stability than the Hellinger deviance test(Simpson 1989). The NEDT is illustrated through an example data set. We also define a goodness-of-fit statistic to assess adequacy of a specified parametric model, and establish its asymptotic normality under the null hypothesis.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.435-443
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• 2005

Coefficients of determination in logistic regression analysis are defined as various statistics, and their values are relatively smaller than those for linear regression model. These coefficients of determination are not generally used to evaluate and diagnose logistic regression model. Liao and McGee (2003) proposed two adjusted coefficients of determination which are robust at the addition of inappropriate predictors and the variation of sample size. In this work, these adjusted coefficients of determination are applied to variable selection method for logistic regression model and compared with results of other methods such as the forward selection, backward elimination, stepwise selection, and AIC statistic.

• The Korean Journal of Applied Statistics
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• v.29 no.3
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• pp.463-470
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• 2016

In analysing a time series on the frequency domain, the spectral estimator (or periodogram) is a very useful statistic to identify the periods of a time series. However, the spectral estimator is very sensitive in nature to outliers, so that the spectral estimator in terms of M-estimation has been studied by some researchers. Pak (2001) proposed an empirical method to choose a tuning parameter for the Huber's M-estimating function. In this article, we try to implement Pak's estimation proposal in the spectral estimator. We use the Korean housing price index as an example data set for comparing various M-estimating results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.2C
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• pp.172-180
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• 2003

This paper propose a new change detection algorithm based on macro block unit for selective video coding scheme. The conventional method badly decides a macro block of unchanged region into a changed macro block due to a noise of the difference images. To solve the problem of the conventional method, we propose a new test statistic which is robust to the noise of the difference image. As shown in experimental results(Fig. 1∼3), the proposed algorithm shows more accurate segmentation results than the conventional method. Also, because the proposed detection method reduces the average numbers of changed macro block per frame to 55∼60% than the conventional method, it can improve the performance of the selective video coding at lower bit rates.